Intelligent, data-driven and grid-stabilizing energy supply management for industrial companies

The gradual decline in traditional energy sources and the simultaneous expansion of renewable energies is increasingly endangering the security of energy supply and leads to strong fluctuations of electricity prices. This poses enormous challenges especially for industrial companies with high energy demand. Against this backdrop, we are currently developing an intelligent, data-driven, and grid-stabilizing energy management platform. Interating self-generation, energy storage, external power purchase, and flexible consumption, the platform ensures not only economically viable control but also grid-stable operation.

The increasing abandonment of nuclear and coal-fired power plants as well as the expansion of photovoltaic and wind power plants are current trends in power generation worldwide. In particular, the growing share of renewable energy sources is increasingly endangering the security of energy supply and leads to strong fluctuations of electricity prices. This poses enormous challenges especially for industrial companies, as rising and strongly fluctuating energy costs have a negative impact on their production costs. Therefore, intelligent energy management solutions are needed which integrate self-generation, energy storage, external power purchase, and flexible consumption. Against this backdrop, we are currently developing an intelligent, data-driven, and grid-stabilizing energy management platform (IDGE Platform) for utility-scale customers. For energy production, the IDGE Platform is able to integrate conventional, e.g., diesel or gas gensets, and renewable energy generation, e.g. photovoltaic systems PV and wind turbines WT, in combination with energy storage BESS, e.g., lithiumIon batteries. Moreover, the platform connects flexible consumers and offers an optional interface to power and energy markets. In order to optimize the generation from an economical perspective and maintain a balance with consumption, we developed and implemented an optimization algorithm which aims to increase power quality, i.e. grid stability, and to reduce the generation costs. To validate and continuously improve the behavior of the IDGE Platform in a real-world application scenario, a demonstrator is set up, which consists of genset, battery storage units, photovoltaic systems, and dynamic loads. The interdisciplinary project team consists of experts from research, i.e., Project Group Business & Information Systems Engineering of the Fraunhofer FIT, and practice, i.e., MAN Energy Solutions and software developer XITASO.